Marine Group II (MGII) archaea are abundant and constitute an ecologically essential portion of marine microbial communities in the upper layers of the ocean, where they make a substantial contribution to organic matter degradation and carbon cycling. Aoguangviridae, which is one of the earliest recognized viral groups linked to MGII archaea, has been detected in a range of marine environments, but its diversity, evolution, and ecological distribution remain unclear. In this work, the diversity and ecology of Aoguangviridae across the global oceans are systematically characterized by integrating global virome resources with metagenomic and metatranscriptomic datasets. Furthermore, a nonredundant genomic dataset compiled from datasets with 59 to 227 genomes, including 168 newly identified uncultivated viral genomes, was expanded. The viruses in this dataset were resolved into 22 subfamilies and 157 genera that displayed conserved modular genome organization. Comparative genomic and phylogenetic analyses identified 7 types of putative auxiliary viral genes and suggested a phylogenetic affinity between representative viral genes and MGII archaeal homologs, which is consistent with a possible host–virus gene exchange. Aoguangviridae are widely distributed across marine and coastal habitats worldwide, with the highest abundance in epipelagic and polar environments. Transcriptional activity was found to vary markedly among lineages and to generally be the highest in the deep chlorophyll maximum layer. Taken together, these findings expand our understanding of the diversity, evolution, biogeography, and transcriptional activity of Aoguangviridae across global oceans.
Coastal shorelines are among the most dynamic and socioeconomically valuable environments on Earth. However, predictions of shoreline change remain constrained by a lack of interdisciplinary integration, poor spatiotemporal validation, insufficient quantification of uncertainties, and spatial data biases. This systematic review, conducted in accordance with PRISMA 2020 guidelines, synthesizes 581 peer-reviewed studies on shoreline prediction indexed in Scopus between 2019 and 2025. The review framework spans influencing factors, monitoring and data acquisition, shoreline extraction methods, quantification frameworks, predictive modeling approaches, and operational applications. Medium-resolution optical satellite platforms dominate observational practice, accounting for 61% of all sensing platforms used in the literature, whereas synthetic aperture radar (7.9%) and unmanned aerial systems (20.6%) remain underutilized, despite their complementary capabilities in dynamic coastal environments. These findings indicate that statistical quantification frameworks remain structurally dependent on linear assumptions, which are fundamentally incompatible with the threshold-driven behavior of real coastal systems. Process-based numerical models are led by XBeach, which accounts for 22.5% of models and demonstrates strong calibration performance but limited forward predictive transferability across sites and forcing conditions. Artificial intelligence applications expanded by 162.5% over the study period, converging toward physics-informed neural networks that directly embed physical conservation laws into model training and achieve the optimal balance between predictive accuracy, interpretability, and computational efficiency. Geographic analysis revealed a pronounced research focus on Asian coastal environments, whereas African and South American coastlines received minimal attention, despite their disproportionate vulnerability to erosion and population exposure. These findings highlight research priorities oriented toward standardized benchmarking, probabilistic forecasting, and transferable hybrid modeling architectures aligned with the United Nations Sustainable Development Goals for climate action, ocean conservation, and sustainable coastal communities.
Storm tracks play a vital role in modulating midlatitude weather and global heat, momentum, and moisture transport. Under global warming, their position and intensity are projected to undergo substantial changes. Using Coupled Model Intercomparison Project Phase 6 simulations, this study examines future storm track responses and the underlying dynamics. Storm tracks are diagnosed using a classical Eulerian metric—synoptic-band (2.5- to 6-d) band-pass-filtered geopotential-height variance—while the mechanisms are quantified through a full-form local eddy kinetic energy budget that partitions baroclinic conversion, barotropic conversion, energy redistribution, and geopotential (pressure) flux convergence. Results show a weakening tendency of Northern Hemisphere storm tracks in June–July–August, consistent with recent evidence of boreal-summer storm track weakening, but a more regionally structured intensification accompanied by a poleward displacement in December–January–February. In the Southern Hemisphere, storm tracks intensify in June–July–August and shift poleward in December–January–February. These changes are linked to enhanced background baroclinicity measured by the Eady growth rate, arising mainly from strengthened meridional temperature gradients with a secondary contribution from changes in static stability. Interpreted through the eddy kinetic energy budget, strengthened high-latitude baroclinic conversion, together with weakened barotropic damping and energy redistribution by flux convergence, supports an upper-tropospheric increase and poleward displacement of transient eddy activity, highlighting the central role of eddy energy conversion and redistribution processes in shaping storm tracks in a warming climate.
